Review of Research on Student-Facing Learning Analytics Dashboards and Educational Recommender Systems
IEEE Transactions on Learning Technologies, 10 (4):
405-418 (October 2017)DOI: 10.1109/TLT.2017.2740172
Abstract
This article is a comprehensive literature review of student-facing learning analytics reporting systems that track learning analytics data and report it directly to students. This literature review builds on four previously conducted literature reviews in similar domains. Out of the 945 articles retrieved from databases and journals, 93 articles were included in the analysis. Articles were coded based on the following five categories: functionality, data sources, design analysis, student perceptions, and measured effects. Based on this review, we need research on learning analytics reporting systems that targets the design and development process of reporting systems, not only the final products. This design and development process includes needs analyses, visual design analyses, information selection justifications, and student perception surveys. In addition, experiments to determine the effect of these systems on student behavior, achievement, and skills are needed to add to the small existing body of evidence. Furthermore, experimental studies should include usability tests and methodologies to examine student use of these systems, as these factors may affect experimental findings. Finally, observational study methods, such as propensity score matching, should be used to increase student access to these systems but still rigorously measure experimental effects.
Description
Review of Research on Student-Facing Learning Analytics Dashboards and Educational Recommender Systems - IEEE Journals & Magazine
Links and resources
Tags
community
@brusilovsky's tags highlighted